This invention relates to after-treatment control schemes and, more particularly, to adapting parameters of a predictive model for estimating the feedgas NOx and CO emissions, and the amount of NOx stored in a Lean NOx Trap (LNT) of a Direct-Injection, Stratified-Charge (DISC) engine system based on real-time HEGO sensor measurements.
DISC engines equipped with a lean NOx trap (LNT) require a sophisticated after-treatment control scheme to manage the LNT purge cycle while responding to driver""s torque demands. In order to effectively manage the activation and deactivation of the LNT purge cycle and optimize fuel economy, a predictive model for feedgas emissions of NOx and CO is used. This emissions model, in combination with a Three-Way Catalyst (TWC) conversion efficiency model and LNT NOx storage/release model, provides a real-time estimate of the NOx stored in the LNT and, therefore, provides a critical input for the engine management system to decide when to start or stop the LNT NOx purge operation. However, because of the complicated nature of the DISC engine operation, the conventional feedgas NOx predictive model cannot be applied.
For a Port Fuel Injection (PFI) or DISC engine with LNT and a HEGO sensor downstream of the LNT, the decision to terminate the purge is made when a HEGO switch is detected. This strategy relies on the detection of HC/CO breakthrough to determine the status of the LNT. The time delay in the system, however, may lead to excess HC and CO in the tailpipe and cause other emission concerns.
Unlike a PFI engine which operates most of the time at stoichiometric air/fuel ratio and whose after-treatment control is achieved primarily by controlling the air/fuel ratio around the stoichiometric value, a DISC engine operates over a wide rage of air/fuel ratios and involves multiple modes of operation. The tailpipe NOx is a function of many engine variables, as well as the present LNT state (the mass of NOx stored in the trap). The performance of a NOx predictive model, which is calibrated off-line to give the best estimation of feedgas NOx, may be susceptible to changes that are due, for example, to engine aging, component-to-component variation, temperature and humidity variation, etc. These changes are relatively slow as compared to engine operating variable changes, and the effects of these changes are usually not incorporated in the model.
In accordance with the present invention, an after-treatment control scheme for managing a LNT purge cycle is disclosed. The control scheme includes a new model structure as well as new algorithms that predict the feedgas NOx emissions for both stratified and homogeneous operating condition. In addition, an adaptive scheme for updating the predictive NOx model based on real-time HEGO sensor measurements is provided to adjust the NOx model to ensure robustness of performance and simplify the model structure. Using a combination of HEGO measurement and NOx model prediction to determine the entry and exit condition for purge operation reduces HC/CO breakthrough, thus improving purge efficiency, emission performance and fuel economy.